Evidence map›Paper›PMID 32033228›Full record

ArticleBiomolecules2020

Bioinformatics Analysis of Global Proteomic and Phosphoproteomic Data Sets Revealed Activation of NEK2 and AURKA in Cancers.

Barnali Deb, Pratyay Sengupta, Janani Sambath, Prashant Kumar

Open access · goldAbstract read
In one paragraph

Article in Biomolecules, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.4field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 25 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 1 country.

Barnali DebInstitute of Bioinformatics, International Technology Park, Bangalore 560066, India.
Pratyay SenguptaDepartment of Biotechnology, National Institute of Technology Durgapur, Mahatma Gandhi Avenue, Durgapur, West Bengal 713209, India.ORCID 0000-0002-0184-9335
Janani SambathInstitute of Bioinformatics, International Technology Park, Bangalore 560066, India.
Prashant KumarInstitute of Bioinformatics, International Technology Park, Bangalore 560066, India.
Manipal Academy of Higher Education · INInstitute of Bioinformatics · INNational Institute of Technology Durgapur · IN

Funding

Department of Science and Technology (DST), Ramanujan Fellowship SB/S2/RJN-077/2015
6 · The paper itself

Abstract

Tumor heterogeneity attributes substantial challenges in determining the treatment regimen. Along with the conventional treatment, such as chemotherapy and radiotherapy, targeted therapy has greater impact in cancer management. Owing to the recent advancements in proteomics, we aimed to mine and re-interrogate the Clinical Proteomic Tumor Analysis Consortium (CPTAC) data sets which contain deep scale, mass spectrometry (MS)-based proteomic and phosphoproteomic data sets conducted on human tumor samples. Quantitative proteomic and phosphoproteomic data sets of tumor samples were explored and downloaded from the CPTAC database for six different cancers types (breast cancer, clear cell renal cell carcinoma (CCRCC), colon cancer, lung adenocarcinoma (LUAD), ovarian cancer, and uterine corpus endometrial carcinoma (UCEC)). We identified 880 phosphopeptide signatures for differentially regulated phosphorylation sites across five cancer types (breast cancer, colon cancer, LUAD, ovarian cancer, and UCEC). We identified the cell cycle to be aberrantly activated across these cancers. The correlation of proteomic and phosphoproteomic data sets identified changes in the phosphorylation of 12 kinases with unchanged expression levels. We further investigated phosphopeptide signature across five cancer types which led to the prediction of aurora kinase A (AURKA) and kinases-serine/threonine-protein kinase Nek2 (NEK2) as the most activated kinases targets. The drug designed for these kinases could be repurposed for treatment across cancer types.

Indexed as

Enzyme ActivationAurora Kinase ACell CycleHumansNeoplasmsNIMA-Related KinasesPhosphoproteinsProtein Interaction MapsProteomicsAURKA protein, humanAurora Kinase ANEK2 protein, humanNIMA-Related KinasesPhosphoproteinsclear cell renal cell carcinomaCPTACdrug targetslung adenocarcinomaphosphorylationuterine corpus endometrial carcinoma

Identifiers

PMID32033228
PMCPMC7072708
OpenAlexW3005213145

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.